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Role Description

You will join a high-visibility initiative focused on maturing the organization's data landscape. The Outpost project is moving from an "evolving" data environment to a structured, high-performance ecosystem. As a Data Architect, your mission is to solve current structural inconsistencies and define the long-term data strategy. This is not a "maintenance" role; it is an architectural leadership position meant to ensure data is reliable, accessible, and high-quality for both internal operational efficiency and external customer reporting. By improving schema performance and structure, you will directly enable better business decisions and robust application performance.

Key Responsibilities

• Define Data Strategy: Architect and implement the long-term data roadmap to transition the organization into a structured, high-performance ecosystem.
• Schema Design: Design and optimize complex data models for both transactional (operational) and analytical use cases.
• Performance Tuning: Lead database performance tuning and structural improvements to ensure high-speed query execution and system reliability.
• Identify Critical Insights: Use analytical intuition to independently identify business-critical data points and define clear analysis goals.
• Standardization: Establish and enforce organizational naming conventions, data governance practices, and structural consistency across the landscape.
• Automation: Utilize Python to create automation scripts for data exploration, cleaning, and landscape management.
• Cross-Functional Collaboration: Partner with Product, Backend Engineering, and Stakeholders to ensure data schemas support both business goals and application UX.

Qualifications

• Advanced SQL Mastery: Expert-level proficiency in query design, CTEs, window functions, and complex aggregations.
• Data Modeling: Proven track record of designing scalable schemas for diverse use cases (Transactional vs. Analytical).
• Optimization Expertise: Deep knowledge of database performance tuning and structural improvements.
• Functional Python: Proficiency in using Python (loops, functions, dictionaries) for data exploration and automation tasks.
• Strategic Intuition: The ability to navigate ambiguity and independently identify how data structure impacts business outcomes.
• Self-Direction: Proven ability to manage complex data landscapes and architectural shifts without constant supervision.
• Fluent English: Strong communication skills for daily collaboration with international stakeholders.

Nice-to-Have Skills

• Cloud Warehousing: Specific experience with Snowflake or similar modern cloud data warehouse environments.
• Governance: Experience implementing formal data governance frameworks and metadata management.
• ETL/ELT Optimization: Hands-on experience optimizing specific data transformation pipelines to reduce latency.
• Modern Data Stack: Familiarity with tools like dbt or Airflow for managing the data lifecycle.
• LATAM Experience: Experience working in remote, distributed teams across Latin American time zones.

Time Zone & Collaboration

The role requires collaboration with teams aligned to Central Time (CT), USA. Candidates must overlap at least 4–5 hours daily with US-based stakeholders to ensure seamless architectural alignment.